On the Role of Emergent Communication for Social Learning in Multi-Agent Reinforcement Learning

Understand

Explicit communication among humans is key to coordinating and learning.

• Social learning, which uses cues from experts, can greatly benefit from the usage of explicit communication to align heterogeneous policies, reduce sample complexity, and solve partially observable tasks.
• Emergent communication, a type of explicit communication, studies the creation of an artificial language to encode a high task-utility message directly from data.
• However, in most cases, emergent communication sends insufficiently compressed messages with little or null information, which also may not be understandable to a third-party listener.